Handbook of Computer Vision Algorithms in Image Algebra

A text introducing engineers, students, and scientists to image algebra, which unifies image transformations, image analysis and image understanding all into one theory. Features an overview of the most commonly used computer algorithms and C++ computer programs that show how image algebra can be converted into computer programs. DLC: Computer vision--Mathematics.

The Handbook of Computer Vision Algorithms in Image Algebra provides over 80 techniques that perform algebraic operations on images. The theoretical basis of image processing made its debut in the early 1950s with von Neumann but it was the technological explosion of the 70s and 80s that image processing hit its full stride. Initially developed for military purposes, these algorithms have applications extending to research and applied disciplines. Image algebra, simply stated, is an image-processing language. It is the mathematical structure by which image fields are interpreted to derive information, such as distance, identification, motion, etc, not to be confused with image enhancement or image creation such as 3-D animation. According to the preface, the authors declare that typos and mathematical errors have been corrected over the first edition. A new chapter on geometric image transformations and exercises at the end of each chapter are further improvements over the first edition. With such significant upgrading, it is advisable to replace the first edition, if it is currently in your collection. Following the preface and acknowledgements, an extensive section on Notation is provided. This is important and its placement at the beginning is fitting. The first chapter is a fine overview of the background and development of image algebra and then the reader is plunged into specific techniques over the next 11 chapters. The appendix contains the actual programming code of the techniques discussed in the book. The book concludes with a perfunctory index. This book is appropriate for collections supporting research programs in theoretical mathematics, computer science research, and engineering. Upper-class undergraduates, graduates and researchers would find this book most useful.Reviewer: Peggy Dominy, Information Services Librarian-Math & Sciences, Drexel University Hagerty Library, dominymf@drexel.edu Copyright 2002 E-Streams Reviews